Frequency and characteristics of <scp>chemotherapy‐associated</scp> thrombotic microangiopathy: Analysis from a large pharmacovigilance database
Authors: Nattawat Klomjit, Richard Evans, Thomas K. Le, Sophia L. Wells, Jessica Ortega, Olivia Green‐Lingren, Marshall Mazepa, Meghan E. Sise, Kenar D. Jhaveri, Shruti Gupta
Journal: American Journal of Hematology (2023)

We used the information component (IC), a disproportionate Bayesian analysis comparing the number of observed versus expected adverse drug reactions, to determine the potential association between anti-neoplastic agents and thrombotic microangiopathy (TMA). The IC025 indicates the lower end of 95% of IC, in which a value >0 suggests a disproportionality signal between the drug of interest and the adverse drug reaction. Carfilzomib had the highest IC025 for TMA among all studied chemotherapies followed by gemcitabine, mitomycin, bevacizumab, and bortezomib. Thrombotic microangiopathies (TMAs) are a heterogenous group of rare, yet life-threatening disorders that are characterized by hemolytic anemia, thrombocytopenia, and end-organ injury, including acute kidney injury (AKI).1 TMA is associated with significant morbidity and mortality2; thus, early recognition is essential. Literature on TMA occurring after certain chemotherapies like gemcitabine and mitomycin,3 and novel agents like targeted therapies (e.g., vascular endothelial growth factor inhibitors [VEGFi] and tyrosine kinase inhibitors [TKIs]), immune checkpoint inhibitors [ICPIs], and proteasome inhibitors [PIs]) are largely limited to case series. Post-marketing, real-world surveillance data can help inform clinicians of the risk profile of different drugs. We used VigiBase, a large global pharmacovigilance database that contains over 20 million individual case safety reports,4 to summarize and compare characteristics and outcomes of TMA after commonly used anti-neoplastic agents. We performed an observational, pharmacovigilance study using VigiBase (Supplemental Methods), which compiles data on medication safety through individual case safety reports that originate from various sources.4 Each safety report represents one patient who has developed the adverse event of interest, and includes information on demographics, drug dosing and drug combinations, and outcomes related to the adverse drug reaction (ADR). We included all reports of "thrombotic microangiopathy," which could be biopsy-proven or cases for which there was a high index of suspicion for TMA. We then searched for anti-neoplastic therapies that have been associated with TMA in the literature.1, 3 These consisted of 38 distinct anti-neoplastic therapies, which were further classified as gemcitabine/mitomycin, PIs, platinum-based chemotherapies, VEGFi/TKIs, ICPIs, and others (bleomycin, docetaxel, doxorubicin, and pentostatin) (Supplemental Methods; Supplemental Table 1). Gemcitabine and mitomycin were examined together as these are the most commonly reported conventional chemotherapies associated with TMA.3 The search also included combinations of any of these pre-specified medications. The query was run on de-duplicated data, whereby suspected duplicates were identified, flagged, and then removed. We hypothesized that certain drug classes, and exposure to a higher number of drug classes (e.g., 1 vs. 2 vs. ≥3), may impact characteristics or outcomes of TMA patients. Drug safety was assessed using the information component (IC), a measure of the disproportionality between the observed and the expected reporting of a drug-ADR pair, to detect ADRs above baseline noise in VigiBase (Supplemental Methods). For this analysis, drugs with a positive (>0) value for IC025 (the lower end of the 95% confidence interval of the IC) were identified as having a signal for TMA within VigiBase (Supplemental Methods). Baseline characteristics, time to onset, indication for anti-neoplastic therapies and outcomes were reported as numbers (with percentages) for categorical variables and median (interquartile ranges) for continuous variables. Time to onset of TMA was examined by drug class if these data were available for at least 20 individuals. All comparisons were two-sided, with p < .05 considered significant. All analyses were performed using R 4.1.2. Between January 1, 2010 and January 15, 2023, there were 31 413 reports of TMA, atypical hemolytic uremic syndrome (aHUS), or thrombotic thrombocytopenic purpura (TTP) (Supplemental Figure 1). After excluding non-TMA ADRs, there were 1712 TMA ADRs across 1099 unique individuals, of whom approximately half were female (n = 498, 45.3%) and from North or South America (n = 507, 46.1%). Most TMA cases (95.2%) were reported after 2014. TMA was most common in the 45–64 years age group (n = 385, 35.3%), and among patients with gastrointestinal and hepatobiliary cancers (n = 327, 29.8%) (Supplemental Table 2). Most patients with TMA received only a single drug class (n = 920, 83.7%), as opposed to 2 classes (n = 152, 13.8%) or ≥3 drug classes (n = 27, 2.5%) (Supplemental Table 2). Gastrointestinal and hepatobiliary cancers were the most common malignancies in TMA cases involving 1 or 2 drug classes, whereas gynecological cancer was the most common among individuals receiving ≥3 drug classes. When assessing the characteristics of TMA by drug class, we found that TMA was most often reported in the setting of treatment with gemcitabine/mitomycin (n = 379, 41.2%) followed by PIs (n = 228, 24.8%), VEGFi/TKIs (n = 185, 20.1%), and platinum-based therapies (n = 76, 8.3%) (Supplemental Figures 2 and 3a). Gemcitabine/mitomycin were the most frequent anti-neoplastic therapies in patients with gastrointestinal, hepatobiliary, gynecologic, and lung cancers, while VEGFi/TKIs were the most common in kidney and urological cancers (Supplemental Figure 3b). There were only adult cases (age ≥ 18 years) reported in the gemcitabine/mitomycin and ICPIs groups, whereas other drug classes reported cases among both pediatric and adult patients (Supplemental Figure 3c). Additional characteristics and demographics by drug class are shown in Supplemental Table 3. Data on time to onset was available in 294 individuals (26.8%). Overall, the median time to onset of TMA was 122 days (interquartile range [IQR] 25–247). Median time to onset of TMA was the shortest for PIs (median 35 days [IQR 8–178]), and the longest for gemcitabine/mitomycin (median 156 days [IQR 91–245]) (Supplemental Figure 4). There were 720 (65.5%) individuals with TMA with outcome data available. Of survivors, 519 (78.3%) were reported as "recovered" or "recovering." TMA in the setting of other chemotherapies had the highest rate of recovery (e.g., either recovered/recovering; n = 14/15; 93.3%), whereas ICPIs were associated with the lowest rate of recovery (n = 3/7, 42.9%). The rates of recovery for PIs, platinums, gemcitabine/mitomycin, and VEGFi/TKIs were 85.8%, 85.3%, 74.4%, and 74.3%, respectively (Supplemental Figures 5a and 5b). There were 57 (5.2%) reported fatalities in the entire cohort. ICPI-TMA had the highest fatality (n = 9, 41.0%), while gemcitabine/mitomycin had the lowest fatality (n = 13, 3.4%) (Supplemental Figure 5b). Finally, we conducted a disproportionality assessment of the 38 anti-neoplastic agents, and found that 30 agents had TMA events reported in VigiBase and 22 agents had an IC025 > 0. Carfilzomib had the highest IC025 at 5.92, followed by gemcitabine (5.52), mitomycin (4.21), bevacizumab (3.63), and bortezomib (3.33) (Figure 1; Supplemental Table 4). In this large pharmacovigilance cohort, we describe the clinical features, timing, and outcomes of TMA after commonly used anti-neoplastic therapies. We used the IC025, which compares the number of observed versus expected adverse drug reactions, to determine the potential association between anti-neoplastic agents and TMA. We found that the drug classes with the highest disproportionality were PIs, gemcitabine/mitomycin, and VEGFi/TKIs. Of all the drug classes that we examined, carfilzomib had the highest IC025, and each of the PIs (carfilzomib, bortezomib, and ixazomib) had a positive IC025. TMA has been reported with gemcitabine and mitomycin in case series,1, 3 and these two drugs had the 2nd and 3rd highest IC025 among studied drugs, respectively. While most of the VEGFi/TKIs, all the platinums, and most of the other chemotherapies had a positive IC025, only two of eight ICPIs with reported TMA in the VigiBase had positive IC025. The reason for this is unclear, and may be due to a lower risk of TMA with these agents, or simply underreporting. PIs have shown promise for the treatment of plasma cell disorders; however, TMA has been reported in case series of patients with multiple myeloma receiving PIs, particularly carfilzomib or ixazomib.5 We found that carfilzomib had the highest IC025 of all studied drugs. Most cases of PI-associated TMA improve with drug discontinuation,5 which was consistent with the relatively high rate of recovery observed in our study. Gemcitabine and mitomycin are commonly associated with TMA3 and had some of the highest IC025 among studied agents in our cohort. Though mitomycin is less commonly used, gemcitabine is still considered a first-line therapy for pancreatic cancer.3 Despite the known association between gemcitabine and TMA, reports of TMA following gemcitabine are largely limited to case series. Patients with gemcitabine-associated TMA often have progressive kidney dysfunction3; thus, understanding characteristics and outcomes of TMA in patients receiving this drug is critical. Time to anti-neoplastic drug-associated TMA is highly variable in case series.1 Interestingly, we found that the median time to onset was only 70 days, perhaps reflecting earlier detection and recognition. Time to TMA onset was the shortest among patients treated with PIs, and the longest among patients receiving gemcitabine/mitomycin. This may be due in part to differences in the pathophysiology of TMA (e.g., immune-mediated vs. dose-dependent toxicity). ICPIs have transformed the landscape of cancer treatment but are also associated with kidney-related adverse events. While we found that 40% of TMA cases improved/recovered, which is consistent with outcomes described in prior studies,1 ICPI-TMA had the highest fatality rate. Case series of ICPI-TMA also suggest that these patients have poor outcomes,6 possibly due to delayed recognition, longer half-life of the drugs, and patient-related factors. Though this is the largest pharmacovigilance study of TMA to date, it has limitations. First, the IC does not imply causality between a particular drug and ADR. Second, granular clinical data are not available in the VigiBase. Third, reports are derived from a variety of sources, including from patients, pharmacists, and others. Fourth, there are no data on the number of patients exposed to the product or drug, and therefore inferences cannot be made with regard to prevalence. Fifth, there may be reporting bias (e.g., most cases originated from North and South America). Sixth, there are limited data on either time to recovery or nature of recovery (e.g., hematologic, renal, or both), or details about cause of death or time to death. Despite these limitations, our study captured over 1000 cases of TMA among patients receiving common anti-neoplastic therapies used for a variety of cancers. Our findings suggest that clinicians should be aware of TMA as a potential complication of both older chemotherapies (e.g., gemcitabine/mitomycin) as well as novel agents like PIs, VEGFi/TKIs, and ICPIs. Additionally, understanding the time to onset of TMA may allow clinicians to maintain a high index of suspicion for TMA and implement targeted preventative or therapeutic strategies. Future prospective studies are needed to better understand and characterize anti-neoplastic therapy-associated TMA. Nattawat Klomjit and Shruti Gupta conceptualized the study, interpreted results, drafted manuscript, and approved the final version of the manuscript. Richard Evans conducted the statistical analysis and approved the final version of the manuscript. Thomas K. Le conceptualized the study design, interpreted results, and approved the final version of the manuscript. Sophia L. Wells, Jessica Ortega, Olivia Green-Lingren, Marshall Mazepa, Meghan E. Sise, and Kenar D. Jhaveri interpreted results, contributed to the manuscript, and approved the final version of the manuscript. We would like to thank VigiBase for providing the data. VigiBase is the WHO global database of reported potential side effects of medicinal products, developed and maintained by Uppsala Monitoring Centre. The information does not represent the opinion of the UMC or the World Health Organization. This work was funded by NIH NIDDK K23DK125672 (to Shruti Gupta). Shruti Gupta reports research support from the NIH, NIDDK K23DK125672. She also reports research funding from BTG International, GE Healthcare, and AstraZeneca outside the submitted work. She is a member of GlaxoSmithKline's (GSK) Global Anemia Council, a consultant for Secretome and Proletariat Therapeutics, and founder of the American Society of Onconephrology. Meghan E. Sise reports research support from the NIH, NIDDK R01DK140839. She also reports research funding from Gilead, Abbvie, EMD-Serono, Angion, and Otsuka outside of the submitted work. She has served on a scientific advisory board for Travere, Novartis, Vera Therapeutics, and Mallinckrodt and is a data monitoring committee member for Alpine Immunosciences. She is on the editorial board of the American Journal of Kidney Disease. Kenar D. Jhaveri reports consultancy agreements with Secretome, George Clinicals, PMV pharmaceuticals, and Calliditas. Kenar D. Jhaveri serves as the US co-national lead for the IgA Nephropathy trial-VISIONARY. Kenar D. Jhaveri reports honoraria from the American Society of Nephrology, Micromedex, and UpToDate.com; reports serving on the editorial boards of the American Journal of Kidney Diseases, CJASN, Clinical Kidney Journal, Journal of Onconephrology, Kidney International, and Nephrology Dialysis Transplantation; reports serving as Editor-in-Chief of ASN Kidney News and section editor for onconephrology for Nephrology Dialysis Transplantation. This data derived from VigiBase which is maintained by Uppsala Monitoring Center, Uppsala, Sweden. Data S1. Supporting Information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.